• Journal of Veterinary Clinics
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• v.14 no.2
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• pp.301-307
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• 1997

These studies were performed to provide some basic informations for developing an automatic system in dairy farming cattle in order that the farmers may easily and automatically detect the maintenance of pregnancy and the fact of abortion of the pregnant cows and also to find out the diseased animals with fever. As a method of automatical detection of the maintenance of pregnancy or the fact of abortion, weighing the pregnant cows was conducted from one month-pregnancy to the term using a digital balance. From the first to the 3rd month of pregnancy the body weight of dairy cows was slowly increased (less than 2% per month), then, relatively high increase (3.4% -4.3% per month) from the fourth to the seventh month followed by decrease (3.3%) in the 8th month and very low increase (0.8-0.9%) from the 9th month to the term were shown, resulting in increase of 128.8 kg (25.05%) of body weight to be compared with the first weight. More than 107, increase of body weight to be compared with the first month-weight was denoted from the 61th month of pregnancy and more than 20% increase from the 7th or the 8th month of pregnancy as wells consequently it was presumed that detection of the maintenance of pregnancy is possible from the 4th or the 5th month of pregnancy. It was possible to diagnose a cow aborted at the 6th month by continual weighing the cow from the 1st month of pregnancy. The calved cows showed considerably higher decrease of body weight even in the third week after parturition (p<0.01)to be compared with the body weight near to the term (81.8-102.0 kg, 14-16% decrease). During the same period of 8months, the pregnant cows gained 127.4 kg (24.78% increase), whereas the non-pregnant cows gained 33.0 kg (0.71% increase) to be compared with the first weight showing considerably higher increase of body weight gain in the pregnant cows than the non-pregnant cows (p<0.01). The statistics of body temperatures of dairy cattle were collected from three clinics including the Teaching Hospital of Chonbuk University and the diseases were classified simply by the major symptoms manifested, denoting the highest temperature in respiratory disease ($39.8{\circ}C$) and the lowest in alimentary disease ($39.6{\circ} C$). These informations of body temperatures were expected to be of value for early and automatical detection of the diseased animals with fever when automatic machinery would be established. The results of periodic weighing the body weight of pregnant cows while milking were also expected to be of great use for the farmers to detect the maintenance of pregnancy and the fact of abortion when the automatic system is established in the near future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.119-131
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• 2024

Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.679-687
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• 2021

The purpose of the present study was to document the standardization and management process of interface terminology regarding the chief complaints, diagnoses, and procedures, including surgery in a four-hospital consortium. The process was proposed, discussed, modified, and finalized in 2016 by the Terminology Standardization Committee (TSC), consisting of personnel from four hospitals. A request regarding interface terminology was classified into one of four categories: 1) registration of a new term, 2) revision, 3) deleting an old term and registering a new term, and 4) deletion. A request was processed in the following order: 1) collecting testimonies from related departments and 2) voting by the TSC. At least five out of the seven possible members of the voting pool need to approve of it. Mapping to the reference terminology was performed by three independent medical information managers. All processes were performed online, and the voting and mapping results were collected automatically. This process made the decision-making process clear and fast. In addition, this made users receptive to the decision of the TSC. In the 16 months after the process was adopted, there were 126 new terms registered, 131 revisions, 40 deletions of an old term and the registration of a new term, and 1235 deletions.

• The KIPS Transactions:PartB
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• v.19B no.2
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• pp.123-126
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• 2012

This paper proposed a method to separate a liver into left and right liver lobes for simple and exact volumetry of the river graft at abdominal MDCT(Multi-Detector Computed Tomography) image before the living donor liver transplantation. A medical team can evaluate an accurate river graft with minimized interaction between the team and a system using this algorithm for ensuring donor's and recipient's safe. On the image of segmented liver, 2 points(PMHV: a point in Middle Hepatic Vein and PPV: a point at the beginning of right branch of Portal Vein) are selected to separate a liver into left and right liver lobes. Middle hepatic vein is automatically segmented using PMHV, and the cutting line is decided on the basis of segmented Middle Hepatic Vein. A liver is separated on connecting the cutting line and PPV. The volume and ratio of the river graft are estimated. The volume estimated using 2 points are compared with a manual volume that diagnostic radiologist processed and estimated and the weight measured during surgery to support proof of exact volume. The mean ${\pm}$ standard deviation of the differences between the actual weights and the estimated volumes was $162.38cm^3{\pm}124.39$ in the case of manual segmentation and $107.69cm^3{\pm}97.24$ in the case of 2 points method. The correlation coefficient between the actual weight and the manually estimated volume is 0.79, and the correlation coefficient between the actual weight and the volume estimated using 2 points is 0.87. After selection the 2 points, the time involved in separation a liver into left and right river lobe and volumetry of them is measured for confirmation that the algorithm can be used on real time during surgery. The mean ${\pm}$ standard deviation of the process time is $57.28sec{\pm}32.81$ per 1 data set ($149.17pages{\pm}55.92$).